Attempt to control efficiency in manufacturing


I. ABSTRACT
Efficiency remains a key component in
manufacturing. Efficiency has been defined for a
long time as the ratio between inputs and outputs.
For many manufacturers achieving process
efficiency becomes a core objective. Efficiency can
only be achieved either by input minimization or by
output maximization. Many production managers
or manufacturing managers have assigned their
competence to the subject. Nevertheless, there are
many constraints to the realization. To develop an
approach in terms of efficiency many industrial
engineers have worked on cost reduction. Even if
reducing the cost can bring a certain level of
outcomes, its effects on quality cannot be ignored.
Some engineers define efficiency as the maximum
result compared to the expected results. However,
in recent analyses and trends in the field, efficiency
is the ability to produce qualitative outputs with
few inputs. In the process of efficiency, many
managers have traded quality for cost saving
pretending to maintain a quality level. Quality and
cost have a direct relationship which means any
change in the quality needs to affect the cost. We
differentiate the analysis of the problem between
quality and cost through a methodic plan. The Plan
is completely set into more practical reasoning
with direct applications. The methodology used in
the process is a stow of cases explaining different
applications necessary for the comprehension of
our critical theory. In Understanding the dilemma
of efficiency, this paper tries to develop an
efficiency control system based on Boolean
algebra. This control system may be related in
many points to different control quality tools.
However, the particularity of this system is the
inclusion of cost factors into the process. The core
focus of apprehension is directed toward a
responsive system. The system is based on
intrusions by understanding each parameter of
efficiency. The most relevant parameters use
notions represented by variables to transform
different information into instructions. The
application of efficiency control is produced
through the correlation between various crucial
concepts. The attempt subsequently describes the
concept used to develop this critical study. As an
attempt, this work can be used as a root to
develop different other applications. The attempt
tries to demonstrate a theory or a notion that can
be disapproved of or criticized. This information
unfastens a door to a better understanding of
efficiency applications in other fields. It reveals the
mind to review some fundamental knowledge. It
helps to develop a modern point of view that can
be applied in automation, manufacturing control,
or even numerical control. As an attempt, this
information will be the first stone as a set of many
others in the vast domain of information
transformation in industrial engineering.
II. INTRODUCTION
1. Problematic
Efficiency incorporates multiple concepts. Some
manufacturers try to apply lean production to their
processes to increase efficiency. Lean production
as a set of principles like value streams tends to
“increase initial costs. Elimination of
manufacturing waste and implementation of
improvement ideas are likely to increase the
maintenance costs” (Oskar Olofsson). Lean
production does not guarantee quality as it does
not have any effect on quality within the process.
There is no pragmatic result that can be directly
applied both in cost and quality. We will define
efficiency as the process of producing at the same
quality as cost reduction. This type of efficiency as
it may be considered does not bring value into the
process. It allows cost savings by reducing other
critical standards like supply quantity and quality.
Thus, “Up until now, manufacturers have been
seeking doable ways to lower costs and boost
Aaron Kusidi Lutete
Attempt to Control Efficiency in Manufacturing
Process
Electronic copy available at: https://ssrn.com/abstract=4433100

productivity in their operations. Many of them
prefer reducing product quality to save production
expenses, but doing so will only hurt their
profitability because customers who aren’t
satisfied will quit buying” (Keyur B). Moreover,
scientific management tools suggest an interesting
approach to efficiency. It talks about efficiency as
the ability to operate at maximum capacity. This
efficiency may be important as you can use the
values stream map to optimize time by removing
unnecessary steps; however, the process may bring
other charges related to the increase of the
working time or may convey a major effect on
quality. Those points represent probabilities that
tend to happen or may occur. There is a distinct
need to find a way to increase efficiency through
cost reduction; however, it is necessary to have a
way to monitor its effect on quality. Furthermore,
it is a competitive choice to increase efficiency
through scientific management and other
processes, but there will nevertheless remain a
need to monitor the effects. The problem of cost
saving and quality through time has become an
important problem for manufacturing. It is
significant to understand that both elements retain
a direct relationship. As shown in the previous
lines, the change in cost directly affects the quality
as much as any change in quality affects the cost.
It is crucial to mention that any positive change in
technology can increase or reduce cost and quality.
It is understood that reducing the cost of material
will automatically reduce the quality outcome and
many manufacturers are engaged to forget the
implication of this relationship. The lack of
efficiency due to the concurrent relationship
between quality and cost is an acute problem. It
should be considered when applying different
production optimization strategies like lean
production. As efficiency depends on these two
subjects, the ideal will be to find a situation of
optimization where there is a maximized quality
function. The cost, on the contrary, is minimized
knowing the two elements have contrasting
functions. As cost depends on variable cost and
fixed cost of production and quality depends on
the process application. An ideal situation can be
challenging to obtain because even if they have a
clear correlation, both functions depend on
numerous other variables. Therefore, the cost
function will be in form of different variables
which will not be accurate in the execution. Many
arguments have been integrated to build a method
or a system of achieving efficiency through quality
and cost. The need of finding a way of achieving
efficiency through management is required more
than before. As a result, a system has been in need
to reduce costs by increasing production quality.
2. Background
Many authors have discussed the problem of
efficiency related to cost and quality. Schmidt-
Ehmcke, Jens, Zloczysti, and Petra, researchers in
German institutions of economic research, develop
an approach to achieving efficiency through linear
programming. For the different authors, the
importance of efficiency in the manufacturing
process will primarily depend on the level of
innovation. Considering the importance of
technology in the field, they have centered their
approach by stressing the impact of innovation on
efficiency. This type of technique emphasizes the
pertinence of field research into new methods of
production. This method can be related to our
current attempt to uncover a more innovative way
to deal with efficiency. However, the authors did
not undoubtedly consider research as part of
innovation. They have considered the change of
equipment or the innovation in terms of materials.
They have also discussed the importance of
efficiency in many countries and manufacturing
areas. The authors demonstrate the engagement of
diverse countries to determine a creative solution
for efficiency. They have gathered much
information on different programs set by countries
to achieve this goal. Gyorgy Kovacs, a software
engineer, discuss the different method of
implementing efficiency and have used three
different methods. The author primarily manages
the application of design to achieve a certain level
of efficiency. The design of the plan can be
significant because removing travel time reduces,
as asserted by the author, waste, labor, and
machine costs. It applies to a certain level because
it is challenging to define the effect of the solution
in terms of quality. The second method used is
efficiency by process optimization. As inferred,
using process optimization through a value stream
map will eliminate unnecessary processes and
reduce costs. However, the author is still not able
to demonstrate the effectiveness of the such
solution in quality. Finally, the author uses lean
production. The author insists on the importance
of automation through implementation and
discusses the consequences of such performance in

quality and quality management. George Emil
Palade from the University of Medicine, Science,
and Technology of Târgu introduces the concept
of the human factor. He introduces the concept in
his scientific article addressing the effect of human
labor on quality and efficiency. The author,
George Emil Palade, is hesitating to different
solutions on efficiency. He concludes that
efficiency can only be achieved through
automation and human labor eradication. This
affirmation or theory embraces the new worldview
of artificial intelligence and increasing automation.
Also, B. Wilson in his book Efficiency of
Manufacturing Systems demonstrates that
efficiency can be obtained through information
control and organization structures. He
implements linear programming to minimize cost
and define quantities of efficiency. However, he
excludes the impact of those quantities on the
quality of final products. Also, “In addition, the
organization structure, engineering team, detailed
processes of dismissal spare parts that use during
downtime hours, MTTR, MTBF. Spare parts
location management, true efficiency, and Net
efficiency in the organization development were
also explained in the article. Zero downtime and
zero losses are explained as decreasing cost
function in operation. Also, another author thinks
that “eliminating non-added values in the processes
using lean management increases organization
production efficiency” (Refaat Hemdan,). M.
McKillop, on the other hand, takes a scientific
management method on efficiency. He goes back
to the roots of time management and operation
management. He insists on the importance of
available time for waste reduction and efficiency.
Also, another "study aims to determine the optimal
cost of quality control as a way to improve cost
efficiency and productivity in the company"
(Achmad Daeng, 5).
III. METHODOLOGY
The importance of any procedure is to define a
road map through methodic strategies. These
strategies are a result of innovative approaches
consulted throughout the research. The first point
of our method is defining the parameters of
efficiency. These parameters are key variables that
will be used in our analysis. In the first few
documents explored, authors are defining
efficiency with different concepts. Each definition
identifies a significant parameter. The first concept
used in efficiency is cost saving. With cost saving,
we understand the different methods used for cost
saving. Some engineer uses stream value or lean
manufacturing to reduce cost and enhance
efficiency. The cost parameter is identified as the
first parameter used in the efficiency analyses. The
cost function tends to be minimized in every
critical study. After the cost parameter, the core
focus of most research has represented quality.
Some researchers suggest that raising quality
arises efficiency. Quality strictly depends on
control and other instructions assigned for quality.
Additionally, Quality remains a parameter that
follows an increasing progression because
manufacturers tend to increase or maximize
quality. As we can notice quality is not defined by
direct variables, it depends on various variables
which can be summarized into one or two factors.
For instance, the quality of some products like
steel is inferred based on factors like rigidity or
resistance. Additionally, there is a certain type of
relationship between the quality and cost
parameters. Both elements defined efficiency either
in their momentum or simultaneously.
Our next step of resolution is to find the
relationship between the two parameters by
defining both functions. There is a certain level of
relationship between the two parameters. The cost
function is defined by variable and fixed costs.
However, the engineer only focuses on variable
costs which tend to be more costly as
economically speaking every fixed cost is subject
to amortization. The variable cost is often defined
as unit cost. The unit cost defines multiple variable
charges. From labor cost to material cost, all
charges are expressed in a single unit. Additionally,
the unit cost is often defined by quantity or time.
The quantity of material or worker and the time
used for work are two composing variables
defining the cost function by a single cost unit. On
the other hand, quality is a more complex function
to define. Many recent studies demonstrate that
quality is a cost. The cost of quality is related to
the cost of the material. The quality of material
defined the quality of the production process. This
means that any variation in cost will directly affect
quality. As both components have a direct
relationship through the single cost unit, it is
important to define the proper way of combining
both elements. These two parameters define a

canal of instruction to develop a system and a
language that understands this correlation.
It is important to define the different variables
which will be used in our research. The first
variable used in different research is the time of
production. Every time spend should be
maximized in production. The time used in the
maintenance of failure raises the cost and
decreases the overall quality of the process. This
element is the variable defining the time between
failure and the time of maintenance. The available
time is a coefficient that defines the current
production time. It is the time spent on
manufacturing activity as maintenance is
considered a cost. Available time should be
increased to reduce costs and increase quality.
Because by increasing available time, we expect to
possess more productive time which will ultimately
affect the quality. Time will be necessary for
developing instruction language by defining either
the quality function or the cost function.
Ultimately, when we talk about a process, we talk
about the operation. Every operation is established
of steps and each step is either numbered or timed.
This type of component fragmentation brings us to
identify the importance of the unique unit concept.
Every element used in manufacturing should be
broken into single units. The sole unit can be a
quantity, a process, a parameter, or a variable.
Each variable has a particular single unit. The
single unit helps individuals to optimize the
process by defining precise measurements needed
for manufacturing. Furthermore, multiple variables
can be used to define quality. It can be a level of
temperature or a certain level of density. The
quality parameter opens us to a variety of variables
that depends on the process and the material used.
After defining the main parameter and different
variables, our next strategy for this investigation
will be to define the conditions of applicability.
The condition of applicability assigns different
variables to the two essential parameters. This
process of assignment defines a certain level of
information used to determine a language. To find
the right language which can directly coordinate
cost and quality, we must consider the direct
relationship between the concept of quality
maximization and cost minimization. The two
functions target a certain logic with binary
outcomes. Boolean algebra is the perfect
mathematical notion to apply to our research
because it deals with binary logic. Before applying
Boolean algebra, we need to transform information
of the two parameters into instruction based on the
desired outcome. As a result, we have set the
desired outcome as "1 “and the undesired outcome
as “0.” Also, we must determine the instruction
operation based on the relationship between the
two parameters and based on the process. This
process is to define whether the variable defining
the parameter is adding or multiplying each other.
That conveys, we must either consider both
commands which means the operation “and (˄)" or
develop an outcome based on at least one
parameter by the operation "or (˅)". The process
of transformation will develop an algorithm for
many other activities.
The language and instruction once set as a system
need to be applied to altered cases. Thus, we
developed a manufacturing case and used actual
practical cases set by Trendniner. These various
cases are used to develop an analysis of every
component and different forms of our theory
application. We have related the theory in different
cases from the processing system to the equipment
process. We have also used visualization to define
and give more tangible proof that efficiency can be
obtained by maximizing quality or monitoring
quality through cost minimization. This algorithm
gives many conclusions based on cost savings and
quality. We have tried to produce some
conclusions by identifying a clear system. This
process of application can be used in other fields
like numerical control. As a six-sigma procedure,
our procedure ends up by controlling finding
defaults and giving some suggestions for future
improvement in the field.
IV. RESULTS
Based on the method developed in our research.
We have seen the application of efficiency
concepts through different case studies. The cases
were either generated or taken from Trendminer, a
control software company. Our results and
conclusion are based on practical cases as evidence
of the applicability and accuracy of our system.
Case 1
In a chocolate manufacturing company, the
supplier has multiple cocoa powder suppliers.
Each supplier has a specified quality and price. The

company requires many inspectors for quality
control. Throughout the process from grinding to
mixing and extruding. The manufacturer needs to
balance the quality of the supplied powder and the
cost. It is required to create an automatic system
to maintain efficiency for production. It is known
that grinding cocoa powder of lower quality tends
to double the grinding process otherwise there will
be a default in the final product. Also, the mixing
of lower quality transfers a heterogenous mixture
which needs to be resent for higher rotation into
the mixer. Finally, the mixture extruder needs to
obtain a certain temperature to avoid default. The
company is using a controller at the end of the
system to control the quality of the process. The
hourly cost of the engineer is more than 12$. Also,
there is an operator working 13$/h between
processes to promote and maintain the default
components. The component is often stocked and
put back in the process to avoid bottlenecks. The
manufacturer cannot determine which supplier
gives a better product because they have numerous
variations to define. The request has been done to
determine the most efficient process for this
product.
a. Solution
To solve this case, we must understand the
different requirements to make this process more
efficient. First, we will need to reduce the machine
time and working time. Knowing that the number
of workers depends on the machine and working
time. We will use the amount of worker 'N' equal
to:
With W: working time.
M: machine time (To: operation time)
Finding the number of workers will help us
understand the necessities which will be needed to
reduce costs. Also, we understand that the
manufacturer often faces a certain period of failure
due to a bottleneck before or after the operator.
We will calculate the available time as:
With MTBF: mean time between failure
MTTR: mean time to repair.
A: Availability
Reducing the cost will be done through time
management by increasing available time. The
availability can be increased by process automation
and failure reduction. We will have to understand
that increasing productivity will have two factors.
First, the manufacturer can be in a semi-automated
level of automation or a fully automated level.
Both levels of automation can be optimized to
have more efficient and time-saving
manufacturing. Besides other changes concerning
the plant organization. The optimization of the
cost will be done through time and labor cost
management. Next, the quality function will be
used as both an independent function and a factor
affecting the cost variable. Because take time
increase with every defect,
quality prevention will optimize the process. Let's
say, the perfect diameter for powder is expressed
in the following table:
Table of diameters (millimeter “mm”)
batch
‘p’ perfect powder
diameter
1 1,2
2 2,4
3 3,4
4 1
5 3,4
6 3,5
7 2,8
8 1,8
9 1,09
10 1,002
11 1,03
12 2,4
13 1,8
14 3,2
15 3,6
Based on this variable, we will determine the range
of perfection or the quality range of the powder in
the grinding process. To find the range “r.” We
will use the formula.
With X: mean value ( )

To observe diameter a plate measurement can be
placed or an optic censor to ensure quality. The
quality range will be between 1.38 mm and
3.42 mm. The cost calculation will be done by
analyzing the least time for the process to finish
the product and the number of workers used for
the process. Assuming the powder circulates at a
certain speed and the time of loading and
unloading. The time to minimize will be:
+M
With A: Availability
T: time function of cost
Tl: loading time.
Tu: unloading time.
vl: Vitesse on the loading process
dl: distance on the loading process
du: distance on the unloading process
the cost function will be determined by c= (N.w) +
T
with (N: number of workers, T: cost Time
function, w: working time)
The automatization of efficiency means that we
will have to reduce N which demonstrates that T
needs to be minimized by the quality range
constraint. It means finding the value of T where
the production achieves quality. Assuming we
have a flow of the lowest value "T" represented in
the table below.
Table of lowest Time
takes Time
(Minutes)
1 30
2 25
3 26.5
4 24
5 22
6 24
7 24.6
8 28.4
9 29.6
10 24.3
11 22.1
12 21.4
13 29
14 28
15 28
Based on the two functions of ranches we must
define the lowest time in which the powder will be
in its range of quality. To do so, we will transform
the two functions into a set of instructions or
assumptions. The assumption or instructions are:
1. The powder achieves its time range of cost
saving: a
2. The powder achieves the diameter range of
quality: b.
Based on the two instructions, we set the
efficiency based on quality as the instruction
(a˄b) if a is in the range (1) and b achieves the
diameter range (1) the product will be able to
move forward. However, if the time range is not
achieved with any approval of the quality sensor,
the product is rejected and put back in the inputs.
The same solution can be applied in the other
process: mixing the extruding.
b. Analysis of the
Solution
The solution to the problem gives us a system that
tends to find quality by a regressive function of
cost. This system is very responsive as it can work
on every level of automation. A visual impact of
the system has been tested through simulations to
see the effectiveness of the conception.
Visual aid from FLEXSIM

Figure1
figure2
The first figure depicts the actual situation and the
different waste of time and quality represented
respectively by (Tw and Qw). Not only is there a
cost of time but also the number of workers
increases the overall cost. The second figure
shows the time we have applied our system
represented by “S”. We can see how we have
increased quality and decreased cost by reducing
the number of workers and the different travel
times.
Applying Boolean algebra to create a control
system based on instruction is a very interesting
notion but we must understand that Boolean
algebra has already been used in many aspects of
manufacturing control. However, in our case, we
use Boolean algebra to find the optimal point of
production or the point of efficiency. These
aspects differentiate our system from other
systems. A control system control quality based on
the parameter of production. However, our control
system includes cost through time management
and quality constraints. This case perfectly
depicted various aspects of application deriving
from our conception.
It is important to understand that there is a certain
condition of applicability to our system. Among
many conditions, two major points need to be
asserted.
1. The first condition is the standard deviation
value. For us to define a range of quality or even a
range of cost savings through time management,
we need to have data with a standard deviation
close to zero. If the standard deviation is zero that
means, the variance will be close to zero and we
will have data that are approximate to each other.
In that case, we will easily define any range of
perfection.
2. The second condition of application is that the
two samples should be correlated which means
that the correlation between a and b must exist. A
test of correlation between the time component
and the diameter should show a clear correlation.
This correlation can be tested with a correlation
test, or we can find the intersection between the
two probabilities. This means that:
P (a∩b) ≠ø this means that
These two conditions define the terms of
applicability of our theory. The conditions may
also be modified according to the type of
production or the variables in the process.
Case 2
This case set a more conceptual example of our
system application. It is a case that was submitted
to Trendminer, a software company. We will
examine the company solution and bring insights
into our results. A reactor that goes from heating
to cooling process is being used for propane
production. The cooling time tends to be
excessively long and costly. There is frequent cost
due to maintenance, failure, or defects. It is firm to
monitor the temperature because of its variation
between batches. The heating time is the process
used to activate the catalyst. The cooling process
is employed to discharge the product. When the
product goes from the heating process to the
cooling process, it frequently results to defect

because the temperature is too high when entering
the cooling point. There is a problem with
temperature monitoring because a temperature
controller tends to maintain failure due to
numerous variations of temperature between
batches. It is proposed to find a solution that will
eventually decrease the cost of the problem.
According to Trendminer engineers, the company
did not possess a valid monitoring tool and did not
have enough data to barely expect a solution. As a
monitoring software company, the first proposition
of the engineer is to find a better control system.
They propose to monitor the process to find the
real problem and to make more analysis. Using
their software, they tracked the evolution of the
temperature. In the temperature frame, different
batches were showing the effects of the heating
process by very high temperatures. By finding that
moment, they have discovered that those moments
can be prevented. The control will be able to see
the defection of temperature through temperature
monitoring.
The Trendminer analysis is centered on finding the
problem and controlling it. However, our solution
starts with that but goes further on to find an
appropriate solution or system to resolve the issue.
Gathering data by monitoring constitutes the first
step of our procedure. Initially, we have a quality
to maintain which obtains the capacity of the
catalyst to discharge properly. The cost function is
the time constraint. First, we want to maximize the
quality to avoid defects and minimize the cost.
Applying our system, the monitoring step will be
the data collection phase. The first thing is to
represent the established condition of probabilities.
To demonstrate the correlation between time and
temperature. If the probability of finding an
ordinary point between the two functions exists. In
our case, we can see that there is a deep
connection between the two elements. There is a
perfect point where we can have a short cooling
time and a perfect discharge propane. To build our
system, we will first build a range of temperatures
that favors quick cooling moments. From the
different data monitored, we will identify the ideal
range favoring the cooling process. Afterward, we
will define the highest temperature for the cooling
process to discharge the product. The two
principal functions will serve as instructions for
our system. We will build a language based on the
two functions. The transition between the heating
and cooling process will be only allowed by
meeting the condition set by the two requirements.
The two functions will act as clear instructions.
These instructions can be numerically controlled
through a control device or can manually be
controlled by selling up a controller with two
temperature devices. The controller will interpret
the devices and open the pipe to the cooling
system once the desired temperature is met on
both sides. Note that the temperature can be
different but in a similar range for different
batches. We will have the system:
The censor will activate the transition only when
the process is catalyzed and can be cooled. The
instructions affirm or reject the action whenever
one of the instructions is unmet. The important
part of this process is that the system is already
used in some numerical control. But the only
particularity is the intelligence given to the system
to both monitor cost and quality with simple
Boolean algebra operations.
We must know that with this system a problem
may be encountered. This process used chemical
reactions in each phase. They depend on a certain
level of concentration in terms of normality. The
mass of the object and the volume greatly change
with the heat effect. This means the quality may be
affected by other different terms related to the
process itself. We must understand the chemical
intervention quality. It can also be included in the
system but will eventually require much more
capacity based on the number of instructions. Also,
we cannot infer material composition was not a
problem. The heating process may be heating to a
certain point that creates a condition in the cooling
system. However. With both assumptions, the
system set will perfectly be reliable to achieve a
certain level of efficiency.
Case 3
AND
Control
system

Trendminer presents another case of value-adding
problems. In the production of water by osmosing.
There is a constraint between energy consumption
and the quality of water produced. When the
energy consumption increase, the water quantity
produced should also increase. It is said that the
energy consumption is due to the number of
parallel skids used simultaneously. A fine of 2200$
is set every time the energy consumption is
abnormally high. The need is to maximize the
process quality which depends on the parallel skid
simultaneous usage.
Trendminer, the software company, applied our
system with different tools. This case clearly
shows that our attempt method can be applied as a
system, a method, or can be applied as a process
system. They monitored the energy consumption
based on the quantity of water circulation in the
skids. By doing so they adjust themselves to the
data collection phase of our system development.
After obtaining the data, they determined the
optimal quantity to run the production with a
certain level of energy. Knowing that the level of
energy should be inferior to the fine level. After
detecting the level of energy, they determined the
quantity corresponding to that level of energy.
This quantity is defined as the optimal cost-saving
quantity. The optimal quantity represents a certain
type of quality value in terms of process cost.
However, the solution to maintaining a system will
be directly introducing the different instructions
into the process instead of determining the optimal
quantity. Censors can be used for both quantity
and energy. Because every batch is different and
the energy limit can change, the instruction will be
set up to allow the pump to open merely when the
quantity of water satisfies the range of optimal
energy. This condition will allow the manufacturer
to be more flexible with its manufacturing process.
The system can be represented as:
I.
V. EFFICIENCY SYSTEM
This attempt to resolve the efficiency problem in
the industry set us to define an efficiency system.
The efficiency system should leverage cost best on
quality. It is a procedure of maximizing quality
with cost constraints. This notion becomes a
system when we can build the connection between
different components and parameters to facilitate
process efficiency.
a) Programming Process
Different steps should be considered to determine
the different elements of the system. These
different steps are the procedure of program
elaboration.
1. Identification of criteria and characteristics: in
this step, we must define the context of the
production. The parameters are key functions
affecting our results. In our cases, we mostly use
two parameters. However, we can have multiple
parameters. The parameter is defined in terms of
function. That function has different variables
which most of the time are interrelated. Those
correlations give the ability to control both
functions using other terms. Also, each variable
can be redefined or defined by a factor that finally
composes all the functions. The most used factor is
time, but other factors can be distance,
temperature, velocity, density, etc.
2. After defining the criteria and diverse functions,
parameters, variables, and factors. We will collect
the data accordingly. First, the data should be
monitored to avoid any misinterpretation of
elements. The data should be collected based on
the two functions and should be defining any
variable or factors directly affecting the function of
the parameter.
3. Defining the range of quality and cost saving: in
this step, the engineer or the concept should
identify the different ranges of optimization. The
range of optimization will be used to create a set
of probabilities to define the correlation or the
interception of the two probabilities. By this time,
we will obtain a system of set language which can
be mathematics language or even proportion
language.
4. Identify the operation. The concept should be
able to identify the different operations based on
the desired outcome and the effective process. For
our attempt, we used Boolean algebraic
operations. The diverse operation also depends on
the factors used and their measurement.
water
pum
p
energy
And(Ʌ)

5. Make the instruction, after defining the
operation, we must define the language of
instruction. Here we have used a binary language.
The most important thing in defining the language
is to know how to automatize the process or the
system. Language in manufacturing will always be
related to the notion of control and automation.
This means that we have to adapt every operation
to other instructions which will be useful by the
language use. The language we are referring to can
be computerized, set as a mechanism, or even use
as signals. The type of language will depend on the
system applicability.
A.
b) Advantage
The first advantage of this system is the reliability
of simple tools. This system does not require any
complex reasoning. The very simple steps can be
applied in many cases of manufacturing. Also, it
gives managers the ability to control industry
efficiency through a dynamic frame of time. It
opens doors to a known understanding of the
relationship between cost and quality. It derived
cost to the time factor which makes it more
efficient to manage and control time. It opens a
crucial vision of the food industry in terms of cost
and quality. It will be more accurate to directly
include the effect of cost on quality instead of
suppressing quality for cost-saving purposes.
Also, it reduces manufacturing costs. This system
reduces manufacturing costs because cost function
is directly integrated into the process through
different factors. By defining cost in terms of time,
we can reduce take time and automatically reduce
the cost. Besides that, we can manage the impact
of cost on certain processes. Cost can also be
defined in terms of energy. As a result, we will
manage costs in terms of calories or watts used.
The cost will be translated into different factors
depending on the case. This aspect gives flexibility
to the cost function because it is most of the time
subject to finances and cost control.
Besides the cost aspect, this system can be applied
in different forms with different tools. It can be
applied in every level of automation from cell to
management automation. This system can be
integrated with every set of automation from
manual manufacturing to semi-automated
machines with censors and indicators. Also, it can
be applied in a fully automated system with a
different range of integration. It can be applied in
different firms from mining to the food industry,
this system is an efficient and simple tool to
implement. Also, it helps to apply efficiency at
every level of production. With this system, you
can apply efficiency in management systems, in the
process, in working environment cases even in
ergonomic cases.
This system is not just a monitoring system. It is a
preventive system. It works perfectly in a process
where the manufacturer went to conditioned
defects. It is used in the production process to
create the perfect condition of optimization for
different elements in the process. It prevents any
form of defect by conditioning the performance of
materials and tools. It makes a point of
optimization by defining the clear performance of
every set or operation taking place in the process.
This type of process conditioned efficiency to the
performance of different operations or tools used.
c) Usage
Different applications can be in:
 Cost and quality management
 Efficiency
 Forecasting many suppliers
 Test production alternatives
 Automation
 Quality content
 Process automation
 Process manufacturing
 System control
 Quality control
 Efficiency control
 Quality standard
d) Inconvenience
The different disadvantages can be.
 The first problem may be the
difficulties to implement the
system as a startup.
 The process may be inaccurate if
the quality is a function of taste.
 The errors due to the relation of
different functions
 The cost of time over accuracy. In
some particular cases,

implementing this system may
increase operation time. However,
the efficiency will increase due to
the increasing index of accuracy.
e) Zone of improvement.
The first zone of improvement is to develop
different instructions for more complex cases or a
broader implementation. For example, different
instructions to create an automated production
system with automated manufacturing support and
manufacturing plant. Also, it is important to
develop more information, and artificial
intelligence can develop more activities in the
background. Because different factors can
influence the process, it is important to monitor
different variations of any factor applied in the
process. Besides that, it is important to have
computer intelligence to analyze other activities
outside of the moment of implementation because
every element in the process should synchronize.
Finally, more propriety can be added to the system
to develop a more complex system. For instance,
more operations can be installed, and different
languages can be used. We can even add more
functions besides quality and cost.
VI. CONCLUSION
The problem of efficiency has become a real
concern in manufacturing. The current
manufacturing world is divided by consumer
tastes. Quality is a factor defining the competition
in the market. Manufacturers, on the other hand,
are more concerned about costless production.
With a contrast between production and the
requirement of different customers, manufacturers
tend to reduce quality to decrease cost. This
concept affects the efficiency of different
manufacturers. The trend becomes a game theory
of rejecting quality for the low cost of production.
To improve the manufacturing process, this
attempt bring insight into a method of achieving
efficiency. Our method strives to achieve efficiency
through quality and cost-function management.
We try differentiating our system by using
concrete analogies based on the application of
Boolean algebra to the diverse function
implemented as instructions. Our attempt to
develop an efficient system has been conclusive
because of the different results. Through our
analyses, our system has shown its applicability at
different times. It has demonstrated a possibility of
a broader system based on efficiency. This
perspective is an unlatched door to further
research on the subject. It has shown efficacy in
control quality and quality prevention. It has also
demonstrated many crucial points on automation.
Besides that, it showed a distinct possibility for the
industry to work more efficiently in this
competitive market where the consumer dictated
the economy.
II. REFERENCES
B, keyur (2023) 13 operational challenges in
manufacturing industry [2022-23 edition],
Plutomen. Available at: https://pluto-
men.com/operational-challenges-in-
manufacturing-industry/ (Accessed: March
7, 2023).
D., M.A.C.K.I.L.L.O.P. (2018) Revival:
Efficiency methods (1917).
Hamdan, N.R. and Hossain, A.M. (2022)
“Applying of lean management to increase
organization efficiency: ‘ABC’ plant case
study,” The International Journal of Science
& Technology, 10(5). Available at:
https://doi.org/10.24940/theijst/2022/v10/i5/
st2205-001.
Kovács, G. (2018) “Methods for efficiency
improvement of production and Logistic
Processes,” Research Papers Faculty of
Materials Science and Technology Slovak
University of Technology, 26(42), pp. 55–
61. Available at:
https://doi.org/10.2478/rput-2018-0006.
OLOFSSON, O.S.K.A.R. (no date) LEAN
MANUFACTURING, IS IT WORTH THE
EFFORT? Lean Manufacturing, is it worth
the effort? Available at: https://world-class-
manufacturing.com/article1.html (Accessed:
March 7, 2023).
Prokopenko, J. and North, K. (no date)
Productivity and Quality Management: A

Modular Programme. Geneva: International
Labour Office - ILO.
Schmidt-Ehmcke, J. and Zloczysti, P. (2009)
“Research efficiency in manufacturing: An
application of DEA at the industry level,”
SSRN Electronic Journal [Preprint].
Available at:
https://doi.org/10.2139/ssrn.1460765.
Sudit, E.F. (1996) Effectiveness, quality, and
efficiency: A management-oriented
approach. Boston: Kluwer Academic
Publishers.
value adding cases (2018) Trendminer software
company. Available at:
https://www.trendminer.com/use-case-
control-fouling-to-improve-asset-availability/
(Accessed: February 25, 2022).

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